Technical Field
The present disclosure generally relates to the field of electronic information retrieval, including the identification and retrieval of point-of-interest information. More specifically, and without limitation, the exemplary embodiments described herein relate to systems and methods for identifying points-of-interest using customized query prediction and execution based on, among other factors, user location and/or other profile data. Computerized systems and methods are also provided for partitioning data for information retrieval.
Background
Electronic mapping has become a useful tool for users to find and navigate to points-of-interest. Users consult electronic maps both to locate known points-of-interest by name or address and to find new points-of-interest that may suit their needs. Electronic mapping applications often include a wealth of point-of-interest information, including business names, phone and address information, hours of operation, reviews, and other useful information. Thus, users may use electronic mapping applications both to find the location and other information about known points-of-interest and discover new points-of-interest that may appeal to them.
In order to enable users to find points-of-interest quickly and efficiently, electronic mapping applications often employ electronic search technology similar to that used for other information retrieval tasks, such as general web searching. However, certain modifications are needed for search algorithms implemented in conjunction with electronic mapping to better to serve the needs to users. For example, query execution and presentation in the electronic mapping context may focus more heavily on the identification and description of points-of-interest that match query terms, rather than on the identification of web pages or other documents that provide detailed information on subjects related to the query terms. Moreover, processing of queries submitted through an electronic mapping application may include analysis of location data corresponding to the user who submitted the query. Thus, query results may be prioritized and presented to the user based on proximity to the user's current location.
Many mobile applications utilize electronic mapping and/or search functionalities. For example, several electronic mapping application providers have developed mobile applications that allow users to access their electronic mapping applications via a mobile phone or tablet. Further, other application developers have incorporated electronic mapping and/or search technology into their applications. For example, applications the facilitate travel accommodations (e.g., car, plane, hotel), restaurant reservations, and general city guides include electronic search and mapping functionalities. Thus, searches conducted on one of these applications may be further refined to include not only location information but also further refinements, such as business type (e.g., restaurant, hotel) and price.
Current systems for providing electronic search functionalities for use with electronic mapping applications suffer from drawbacks or disadvantages that affect their ability efficiently to provide meaningful information to users. For example, current electronic search technologies do not provide adequate customization for client applications in the electronic mapping context. Current systems also take too long to provide users with desired point-of-interest information. For example, users may need to type very detailed search queries or perform numerous queries in order to obtain the desired results. Moreover, the results are not displayed to the user until the user completes the query and even then may not include the information that the user desires to see for a given point-of-interest. Although relevant for any search and/or mapping application, these concerns are particularly relevant in the mobile application context, as users' ability to craft queries is limited by hardware capabilities of mobile devices (e.g., screen or keyboard size).